Estimating dissolved carbon concentrations in global soils: a global database and model
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2020-09-04
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Abstract
Dissolved carbon (C) leaching in and from soils plays an important role in C transport along the terrestrial-aquatic continuum. However, a global overview and analysis of dissolved carbon in soil solutions, covering a wide range of vegetation types and climates, is lacking. We compiled a global database on annual average dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) in soil solutions, including potential governing factors, with 762 entries from 351 different sites covering a range of climate zones, land cover types and soil classes. Using this database we develop regression models to calculate topsoil concentrations, and concentrations versus depth in the subsoil at the global scale. For DIC, the lack of a proportional globally distributed cover inhibits analysis on a global scale. For DOC, annual average concentrations range from 1.7 to 88.3 (median = 25.27) mg C/L for topsoils (n = 255) and from 0.42 to 372.1 (median = 5.50) mg C/L for subsoils (n = 285, excluding lab incubations). Highest topsoil values occur in forests of cooler, humid zones. In topsoils, multiple regression showed that precipitation is the most significant factor. Our global topsoil DOC model (R 2= 0.36) uses precipitation, soil class, climate zone and land cover type as model factors. Our global subsoil model describes DOC concentrations vs. depth for different USDA soil classes (overall (R 2= 0.45). Highest subsoil DOC concentrations are calculated for Histosols.
Keywords
Carbon leaching, Database, DIC, DOC, Global model, Soil carbon, Soil solution, Vadose zone, General Engineering, General Environmental Science, General Materials Science, General Physics and Astronomy, General Chemical Engineering, General Earth and Planetary Sciences
Citation
Langeveld, J, Bouwman, A F, van Hoek, W J, Vilmin, L, Beusen, A H W, Mogollón, J M & Middelburg, J J 2020, 'Estimating dissolved carbon concentrations in global soils : a global database and model', SN Applied Sciences, vol. 2, no. 10, 1626. https://doi.org/10.1007/s42452-020-03290-0